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Direction-Adaptive Discrete Wavelet Transform for Image Compression

机译:方向自适应离散小波变换的图像压缩

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摘要

We propose a direction-adaptive DWT (DA-DWT) that locally adapts the filtering directions to image content based on directional lifting. With the adaptive transform, energy compaction is improved for sharp image features. A mathematical analysis based on an anisotropic statistical image model is presented to quantify the theoretical gain achieved by adapting the filtering directions. The analysis indicates that the proposed DA-DWT is more effective than other lifting-based approaches. Experimental results report a gain of up to 2.5 dB in PSNR over the conventional DWT for typical test images. Subjectively, the reconstruction from the DA-DWT better represents the structure in the image and is visually more pleasing.
机译:我们提出了一种方向自适应的DWT(DA-DWT),它可以根据方向提升将过滤方向局部适应图像内容。通过自适应变换,可以改善能量压缩,以获得清晰的图像特征。提出了基于各向异性统计图像模型的数学分析,以量化通过调整滤波方向而获得的理论增益。分析表明,提出的DA-DWT比其他基于提升的方法更有效。实验结果表明,对于典型的测试图像,与传统的DWT相比,PSNR的增益高达2.5 dB。从主观上讲,通过DA-DWT进行的重建可以更好地表示图像中的结构,并且在视觉上更令人愉悦。

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